## Copyright (C) 2022 Nicholas R. Jankowski
## Copyright (C) 2012 Rik Wehbring
## Copyright (C) 1997-2016 Kurt Hornik
##
## This program is free software: you can redistribute it and/or
## modify it under the terms of the GNU General Public License as
## published by the Free Software Foundation, either version 3 of the
## License, or (at your option) any later version.
##
## This program is distributed in the hope that it will be useful, but
## WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
## General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; see the file COPYING. If not, see
## .
## -*- texinfo -*-
## @deftypefn {} {} hygecdf (@var{x}, @var{t}, @var{m}, @var{n})
## Compute the cumulative distribution function (CDF) at @var{x} of the
## hypergeometric distribution with parameters @var{t}, @var{m}, and @var{n}.
##
## This is the probability of obtaining not more than @var{x} marked items
## when randomly drawing a sample of size @var{n} without replacement from a
## population of total size @var{t} containing @var{m} marked items.
##
## The parameters @var{t}, @var{m}, and @var{n} must be positive integers
## with @var{m} and @var{n} not greater than @var{t}.
## @end deftypefn
## Author: KH
## Description: CDF of the hypergeometric distribution
function cdf = hygecdf (x, t, m, n)
if (nargin != 4)
print_usage ();
endif
if (! isscalar (t) || ! isscalar (m) || ! isscalar (n))
[retval, x, t, m, n] = common_size (x, t, m, n);
if (retval > 0)
error ("hygecdf: X, T, M, and N must be of common size or scalars");
endif
endif
if (iscomplex (x) || iscomplex (t) || iscomplex (m) || iscomplex (n))
error ("hygecdf: X, T, M, and N must not be complex");
endif
if (isa (x, "single") || isa (t, "single")
|| isa (m, "single") || isa (n, "single"))
cdf = NaN (size (x), "single");
else
cdf = NaN (size (x));
endif
ok = ((t >= 0) & (m >= 0) & (n > 0) & (m <= t) & (n <= t) &
(t == fix (t)) & (m == fix (m)) & (n == fix (n)));
if (isscalar (t))
if (ok)
cdf = discrete_cdf (x, 0 : n, hygepdf (0 : n, t, m, n));
endif
else
ok &= ! isnan (x);
n = n(ok);
num_n = numel (n);
v = 0 : max (n(:));
## manually perform discrete_cdf to enable vectorizing with array input
p = cumsum (hygepdf (v, t(ok), m(ok), n, "vectorexpand"), 2);
sz_p = size (p);
end_locs = sub2ind (sz_p, [1 : num_n]', n(:) + 1);
p ./= (p(end_locs));
v_col_idx = min (lookup (v, x(ok)(:)) + 1, n(:) + 2);
cdf(ok) = [zeros(num_n, 1), p](sub2ind (sz_p + [0,1], ...
[1 : num_n]', v_col_idx));
endif
endfunction
%!shared x,y
%! x = [-1 0 1 2 3];
%! y = [0 1/6 5/6 1 1];
%!assert (hygecdf (x, 4*ones (1,5), 2, 2), y, eps)
%!assert (hygecdf (x, 4, 2*ones (1,5), 2), y, eps)
%!assert (hygecdf (x, 4, 2, 2*ones (1,5)), y, eps)
%!assert (hygecdf (x, 4*[1 -1 NaN 1.1 1], 2, 2), [y(1) NaN NaN NaN y(5)], eps)
%!assert (hygecdf (x, 4, 2*[1 -1 NaN 1.1 1], 2), [y(1) NaN NaN NaN y(5)], eps)
%!assert (hygecdf (x, 4, 5, 2), [NaN NaN NaN NaN NaN])
%!assert (hygecdf (x, 4, 2, 2*[1 -1 NaN 1.1 1]), [y(1) NaN NaN NaN y(5)], eps)
%!assert (hygecdf (x, 4, 2, 5), [NaN NaN NaN NaN NaN])
%!assert (hygecdf ([x(1:2) NaN x(4:5)], 4, 2, 2), [y(1:2) NaN y(4:5)], eps)
## Test class of input preserved
%!assert (hygecdf ([x, NaN], 4, 2, 2), [y, NaN], eps)
%!assert (hygecdf (single ([x, NaN]), 4, 2, 2), single ([y, NaN]), eps ("single"))
%!assert (hygecdf ([x, NaN], single (4), 2, 2), single ([y, NaN]), eps ("single"))
%!assert (hygecdf ([x, NaN], 4, single (2), 2), single ([y, NaN]), eps ("single"))
%!assert (hygecdf ([x, NaN], 4, 2, single (2)), single ([y, NaN]), eps ("single"))
## Test input validation
%!error hygecdf ()
%!error hygecdf (1)
%!error hygecdf (1,2)
%!error hygecdf (1,2,3)
%!error hygecdf (1,2,3,4,5)
%!error hygecdf (ones (2), ones (3), 1, 1)
%!error hygecdf (1, ones (2), ones (3), 1)
%!error hygecdf (1, 1, ones (2), ones (3))
%!error hygecdf (i, 2, 2, 2)
%!error hygecdf (2, i, 2, 2)
%!error hygecdf (2, 2, i, 2)
%!error hygecdf (2, 2, 2, i)